In the visual system, the information transmitted from the retina is analyzed and transformed by the visual cortex at multiple stages to construct an internal representation of the environment. It has long been suggested that the visual cortex is a passive filter that creates a static, spatial, representation of a visual scene via a hierarchical processing of sensory inputs from the two eyes. According to this view, variations in neuronal responses to identical stimuli were believed to reflect stochastic fluctuations, or noise. However, this view largely ignores the fact that, even when the eyes are closed, the brain is far from being silent. Indeed, several lines of evidence indicate that fluctuations in population activity cause cortical networks to wander through various states of excitability. Although it is acknowledged that fluctuations in ongoing activity change the state of cortical networks involved in stimulus processing, little is known about whether and how cortical states interact with incoming stimuli to influence visual representations, and subsequently behavioral performance. This proposal will examine the relationship between fluctuations in the ongoing activity of neurons in primary visual cortex (V1) and orientation coding (Aim 1), the influence of ongoing activity on the ability of populations of neurons to reliably encode orientation signals (Aim 2), and the relationship between ongoing activity, stimulus-evoked response, and behavioral performance during orientation discrimination (Aim 3). We believe that our research on state-dependent information processing in visual cortex has the potential to advance our understanding of the neuronal mechanisms underlying visual perception and learning, and, at the same time, help develop chronically-implantable human cortical prostheses to assist visually impaired people.